With increasingly high penetrations of PV on distribution systems, there can be many benefits and impacts to the standard operation of the grid. This paper focuses on voltages below the allowable range caused by the installation of PV on distribution systems with line-drop compensation enabled voltage regulation controls. This paper demonstrates how this type of under-voltage issue has the potential to limit the hosting capacity of PV on a feeder and have possible consequences to other feeders served off a common regulated bus. Some examples of mitigation strategies are presented, along with the shortcomings of each. An example of advanced inverter functionality to mitigate overvoltage is shown, while also illustrating the ineffectiveness of inverter voltage control as a mitigation of under-voltage.
To address the lack of knowledge of local solar variability, we have developed, deployed, and demonstrated the value of data collected from a low-cost solar variability sensor. While most currently used solar irradiance sensors are expensive pyranometers with high accuracy (relevant for annual energy estimates), low-cost sensors display similar precision (relevant for solar variability) as high-cost pyranometers, even if they are not as accurate. In this work, we list variability sensor requirements, describe testing of various low-cost sensor components, present a validation of an alpha prototype, and show how the variability sensor collected data can be used for grid integration studies. The variability sensor will enable a greater understanding of local solar variability, which will reduce developer and utility uncertainty about the impact of solar photovoltaic installations and thus will encourage greater penetrations of solar energy.
To address the lack of knowledge of local solar variability, we have developed, deployed, and demonstrated the value of data collected from a low-cost solar variability sensor. While most currently used solar irradiance sensors are expensive pyranometers with high accuracy (relevant for annual energy estimates), low-cost sensors display similar precision (relevant for solar variability) as high-cost pyranometers, even if they are not as accurate. In this work, we list variability sensor requirements, describe testing of various low-cost sensor components, present a validation of an alpha prototype, and show how the variability sensor collected data can be used for grid integration studies. The variability sensor will enable a greater understanding of local solar variability, which will reduce developer and utility uncertainty about the impact of solar photovoltaic installations and thus will encourage greater penetrations of solar energy.
Utilities issuing new PV interconnection permits must be aware of any risks caused by PV on their distribution networks. One potential risk is the degradation of the effectiveness of the network's protection devices (PDs). This can limit the amount of PV allowed in the network, i.e. the network's PV hosting capacity. This research studies how the size and location of a PV installation can prevent network PDs from operating as intended. Simulations are carried out using data from multiple actual distribution feeders in OpenDSS. The PD TCC are modeled to find the timing of PD tripping to accurately identify when PV will cause unnecessary customer outages. The findings show that more aggressive protection settings limit the amount of PV that can be placed on a network that does not cause more customer outages or damage network equipment.
Most utilities use a standard small generator interconnection procedure (SGIP) process that includes a screen for placing potential PV interconnection requests on a fast track that do not require more detailed study. One common screening threshold is the 15% of peak load screen that fast tracks PV below a certain size. This paper performs a technical evaluation of the screen compared to a large number of simulation results for PV on 40 different feeders. Three error metrics are developed to quantify the accuracy of the screen for identifying interconnections that would cause problems or incorrectly sending a large number of allowable systems for more detailed study.
The third solicitation of the California Solar Initiative (CSI) Research, Development, Demonstration and Deployment (RD&D) Program established by the California Public Utility Commission (CPUC) is supporting the Electric Power Research Institute (EPRI), National Renewable Energy Laboratory (NREL), and Sandia National Laboratories (SNL) with collaboration from Pacific Gas and Electric (PG&E), Southern California Edison (SCE), and San Diego Gas and Electric (SDG&E), in research to improve the Utility Application Review and Approval process for interconnecting distributed energy resources to the distribution system. Currently this process is the most time - consuming of any step on the path to generating power on the distribution system. This CSI RD&D solicitation three project has completed the tasks of collecting data from the three utilities, clustering feeder characteristic data to attain representative feeders, detailed modeling of 16 representative feeders, analysis of PV impacts to those feeders, refinement of current screening processes, and validation of those suggested refinements. In this report each task is summarized to produce a final summary of all components of the overall project.
Increasing number s of PV on distribution systems are creating more grid impacts , but it also provides more opportunities for measurement, sensing, and control of the grid in a distributed fashion. This report demonstrates three software tools for characterizing and controlling distribution feeders by utilizing large numbers of highly distributed current, voltage , and irradiance sensors. Instructions and a user manual is presented for each tool. First, the tool for distribution system secondary circuit parameter estimation is presented. This tool allows studying distribution system parameter estimation accuracy with user-selected active power, reactive power, and voltage measurements and measurement error levels. Second, the tool for multi-objective inverter control is shown. Various PV inverter control strategies can be selected to objectively compare their impact on the feeder. Third, the tool for energy storage for PV ramp rate smoothing is presented. The tool allows the user to select different storage characteristics (power and energy ratings) and control types (local vs. centralized) to study the tradeoffs between state-of-charge (SOC) management and the amount of ramp rate smoothing.
Many utilities today have a large number of interconnection requests for new PV installations on their distribution networks. Interconnections should be approved in a timely manner but without compromising network reliability. It is thus important to know a network's PV hosting capacity, which defines the upper bound of PV sizes that pose no risk to the network. This paper investigates how implementing reactive power control on the PV inverter impacts the PV hosting capacity of a distribution network. A local Volt-Var droop control is used and simulations are performed in OpenDSS and Matlab. Multiple feeders are tested and it is found that the control greatly improves the overall hosting capacity of the feeder as well as the locational hosting capacity of most voltage constrained buses.
Many utilities today have a large number of interconnection requests for new PV installations on their distribution networks. Interconnections should be approved in a timely manner but without compromising network reliability. It is thus important to know a network's PV hosting capacity, which defines the upper bound of PV sizes that pose no risk to the network. This paper investigates how implementing reactive power control on the PV inverter impacts the PV hosting capacity of a distribution network. A local Volt-Var droop control is used and simulations are performed in OpenDSS and Matlab. Multiple feeders are tested and it is found that the control greatly improves the overall hosting capacity of the feeder as well as the locational hosting capacity of most voltage constrained buses.
This project is part of the third solicitation of the California Solar Initiative (CSI3) Research, Development, Demonstration, and Deployment Program created by the California Public Utilities Commission (CPUC) in 2006 to support solar research in California. The program focuses on research to improve the utility application review and approval process for interconnecting distributed energy resources such as solar to the distribution system. The CSI3 program is supporting EPRI, National Renewable Energy Laboratory (NREL), and Sandia National Laboratories (SNL) in their collaboration on the process with Pacific Gas and Electric (PG&E), Southern California Edison (SCE), and San Diego Gas and Electric (SDG&E). At present, the application review and approval process is the most time-consuming of any step on the path to generating power for delivery through the distribution system.
To analyze and coordinate the operation of distribution systems with rapidly increasing amounts of PV, more accurate distribution system models are required, especially for the distribution system secondary (low-voltage) circuits down to the point of common coupling for distributed PV. There is a growing need for automated procedures to calibrate the distribution system secondary circuit models that are typically either not modeled at all or are modeled with a lower level of detail than the better modeled medium-voltage systems. This report presents an accurate, flexible, and computationally efficient method to use measurement data to estimate secondary circuit series impedance parameters in existing utility feeder models. The parameter estimation method assumes well-modeled primary circuit models, known secondary circuit topologies, and AMI active power, and reactive power measurements at all the loads in the secondary circuit. The method also requires AMI voltage measurement at most of the loads in the secondary circuit but can handle loads that do not have voltage measurements. No existing secondary circuit model information is needed, except for topology. The method is based on the well-known linearized voltage drop approximation and linear regression. The performance of the method is demonstrated on a three-phase test circuit with ten different secondary circuit topologies and on the Georgia Tech campus distribution system with AMI data. The developed method can be utilized to improve existing utility feeder models for more accurate analysis and operation with ubiquitous distributed PV interconnected on the low-voltage circuits.
Peppanen, Jouni; Reno, Matthew J.; Thakkar, Mohini; Grijalva, Santiago; Harley, Ronald G.
The many new distributed energy resources being installed at the distribution system level require increased visibility into system operations that will be enabled by distribution system state estimation (DSSE) and situational awareness applications. Reliable and accurate DSSE requires both robust methods for managing the big data provided by smart meters and quality distribution system models. This paper presents intelligent methods for detecting and dealing with missing or inaccurate smart meter data, as well as the ways to process the data for different applications. It also presents an efficient and flexible parameter estimation method based on the voltage drop equation and regression analysis to enhance distribution system model accuracy. Finally, it presents a 3-D graphical user interface for advanced visualization of the system state and events. Moreover, we demonstrate this paper for a university distribution network with the state-of-the-art real-time and historical smart meter data infrastructure.
Accurately representing the local solar variability at timescales relevant to distribution grid operations (30-s and shorter) is essential to modeling the impact of solar photovoltaics (PV) on distribution feeders. Due to a lack of available high-frequency solar data, some distribution grid studies have used synthetically-created PV variability or measured PV variability from a different location than their study location. In this work, we show the importance of using accurate solar PV variability inputs in distribution studies. Using high-frequency solar irradiance data from 10 locations in the United States, we compare the ramp rate distributions at the different locations, use a quantitative metric to describe the solar variability at each location, and run distribution simulations using representative 1-week samples from each location to demonstrate the impact of locational solar variability on the number of voltage regulator tap change operations. Results show more than a factor of 3 difference in the number of tap change operations between different PV power variability samples based on irradiance from the different locations. Errors in simulated number of tap changes of up to -70% were found when using low-frequency (e.g., 15-min) solar variability.
This manual provides the documentation of the MATLAB toolbox of functions for using OpenDSS to simulate the impact of solar energy on the distribution system. The majority of the functio ns are useful for interfacing OpenDSS and MATLAB, and they are of generic use for commanding OpenDSS from MATLAB and retrieving information from simulations. A set of functions is also included for modeling PV plant output and setting up the PV plant in th e OpenDSS simulation. The toolbox contains functions for modeling the OpenDSS distribution feeder on satellite images with GPS coordinates. Finally, example simulations functions are included to show potential uses of the toolbox functions. Each function i n the toolbox is documented with the function use syntax, full description, function input list, function output list, example use, and example output.